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Reformulation of a combinatorial problem into optimization of a statistical-mechanics system, enables finding a better solution using heuristics derived from a physical process, such as by the SA (Simulated Annealing). In this paper, we…

Computational Physics · Physics 2017-06-28 Andriyan Bayu Suksmono

We describe a simple, efficient method for simulating Hamiltonian dynamics on a quantum computer by approximating the truncated Taylor series of the evolution operator. Our method can simulate the time evolution of a wide variety of…

Quantum Physics · Physics 2015-03-06 Dominic W. Berry , Andrew M. Childs , Richard Cleve , Robin Kothari , Rolando D. Somma

The dynamics of a one-degree of freedom oscillator with arbitrary polynomial non-linearity subjected to an external periodic excitation is studied. The sequences (cascades) of harmonic and subharmonic stationary solutions to the equation of…

Chaotic Dynamics · Physics 2015-01-28 Vasyl P. Lukomsky , Ivan S. Gandzha

Slow feature analysis (SFA) is a method for extracting slowly varying features from a quickly varying multidimensional signal. An open source Matlab-implementation sfa-tk makes SFA easily useable. We show here that under certain…

Machine Learning · Statistics 2009-12-08 Wolfgang Konen

The quadratic assignment problem (QAP) is one of the most difficult combinatorial optimization problems. One of the most powerful and commonly used heuristics to obtain approximations to the optimal solution of the QAP is simulated…

Neural and Evolutionary Computing · Computer Science 2011-11-08 Gerald Paul

The violent relaxation and the metastable states of the Hamiltonian Mean-Field model, a paradigmatic system of long-range interactions, is studied using a Hamiltonian formalism. Rigorous results are derived algebraically for the time…

Chaotic Dynamics · Physics 2009-10-29 Romain Bachelard , Cristel Chandre , Antonia Ciani , Duccio Fanelli , Yoshiyuki Yamaguchi

This work proposes a simple yet effective sampling framework for combinatorial optimization (CO). Our method builds on discrete Langevin dynamics (LD), an efficient gradient-guided generative paradigm. However, we observe that directly…

Machine Learning · Computer Science 2025-12-22 Shengyu Feng , Yiming Yang

This work studies the symmetries, the associated momentum map, and relative equilibria of a mechanical system consisting of a small axisymmetric magnetic body-dipole in an also axisymmetric external magnetic field that additionally exhibits…

Symplectic Geometry · Mathematics 2013-11-12 Lyudmila Grigoryeva , Juan-Pablo Ortega , Stanislav Zub

A linear stability analysis of the hydrodynamic equations of a model for confined quasi-two-dimensional granular gases is carried out. The stability analysis is performed around the homogeneous steady state (HSS) reached eventually by the…

Statistical Mechanics · Physics 2021-06-10 Vicente Garzó , Ricardo Brito , Rodrigo Soto

This paper studies the nonlinear evolution of magnetic field turbulence in proximity of steady ideal MHD configurations characterized by a small electric current, a small plasma flow, and approximate flux surfaces, a physical setting that…

Plasma Physics · Physics 2024-09-12 Naoki Sato , Michio Yamada

Convex relaxation methods are powerful tools for studying the lowest energy of many-body problems. By relaxing the representability conditions for marginals to a set of local constraints, along with a global semidefinite constraint, a…

Optimization and Control · Mathematics 2025-07-15 Yi Wang , Rizheng Huang , Yuehaw Khoo

An analytical method for investigation of the evolution of dynamical systems {\it with independent on time accuracy} is developed for perturbed Hamiltonian systems. The error-free estimation using of computer algebra enables the application…

Instrumentation and Methods for Astrophysics · Physics 2016-12-13 A. V. Gurzadyan , A. A. Kocharyan

Hybrid dynamical systems have proven to be a powerful modeling abstraction, yet fundamental questions regarding the dynamical properties of these systems remain. In this paper, we develop a novel class of relaxations which we use to recover…

Dynamical Systems · Mathematics 2017-10-25 Tyler Westenbroek , S. Shankar Sastry , Humberto Gonzalez

Sample average approximation (SAA) is a widely popular approach to data-driven decision-making under uncertainty. Under mild assumptions, SAA is both tractable and enjoys strong asymptotic performance guarantees. Similar guarantees,…

Optimization and Control · Mathematics 2016-11-03 Dimitris Bertsimas , Vishal Gupta , Nathan Kallus

Non-homogeneous hidden Markov models (NHHMM) are a subclass of dependent mixture models used for semi-supervised learning, where both transition probabilities between the latent states and mean parameter of the probability distribution of…

Machine Learning · Statistics 2019-12-23 Aliaksandr Hubin

We propose and study a version of simulated annealing (SA) on continuous state spaces based on $(t,s)_R$-sequences. The parameter $R\in\bar{\mathbb{N}}$ regulates the degree of randomness of the input sequence, with the case $R=0$…

Computation · Statistics 2016-09-06 Mathieu Gerber , Luke Bornn

The search for solutions of field theories allowing for topological solitons requires that we find the field configuration with the lowest energy in a given sector of topological charge. The standard approach is based on the numerical…

High Energy Physics - Theory · Physics 2009-10-31 Mark Hale , Oliver Schwindt , Tom Weidig

The recently-introduced relaxation approach for Runge-Kutta methods can be used to enforce conservation of energy in the integration of Hamiltonian systems. We study the behavior of implicit and explicit relaxation Runge-Kutta methods in…

Numerical Analysis · Mathematics 2020-07-13 Hendrik Ranocha , David I. Ketcheson

A global optimization method, conformational space annealing (CSA), is applied to study a 46-residue protein with the sequence B_9N_3(LB)_4N_3B_9N_3(LB)_5L, where B, L and N designate hydrophobic, hydrophilic, and neutral residues,…

Statistical Mechanics · Physics 2009-11-10 Seung-Yeon Kim , Sung Jong Lee , Jooyoung Lee

Hyperexponential stability is investigated for dynamical systems with the use of both, explicit and implicit, Lyapunov function methods. A nonlinear hyperexponential control is designed for stabilizing linear systems. The tuning procedure…

Systems and Control · Electrical Eng. & Systems 2022-07-19 Konstantin Zimenko , Denis Efimov , Andrey Polyakov
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